Tumor-infiltrating PD1-Positive Lymphocytes and FoxP3-Positive Regulatory T Cells Predict Distant Metastatic Relapse and Survival of Clear Cell Renal Cell Carcinoma

BACKGROUND: Clear cell renal cell carcinoma (CRCC) is the most common malignant tumor of the kidney, and the clinical outcome of CRCC is related with the metastatic potential of CRCC. A significant proportion of metastatic CRCC remains incurable. Recently, immunotherapy against specific targets such as programmed death 1 (PD1) has been adapted for fatal cases of CRCC. MATERIALS AND METHODS: In this study, we aimed to evaluate the potential of tumor-infiltrating PD1-positive lymphocytes or FoxP3-positive regulatory T cells (Tregs) as predictors of the metastatic potential or prognosis of CRCC and investigate possible correlations with Epstein-Barr virus (EBV) infection in 199 cases of CRCC. RESULTS: PD1 positivity, high Treg number, and EBV infection all predicted poor overall survival (OS) by univariate analysis. PD1 positivity and high Treg numbers were also significantly correlated with more distant metastatic relapse (DMR) and poor relapse-free survival (RFS) by univariate analysis. PD1 positivity and high Treg number were independent prognostic indicators for OS. In addition, PD1 positivity was an independent predictor of RFS and DMR. EBV infection was an independent predictor of OS of CRCC. CONCLUSION: This study demonstrates that intratumoral infiltration of PD1-positive or FoxP3-positive lymphocytes can be used as significant prognostic indicators of CRCC and PD1 positivity could be very helpful in the prediction of latent distant metastasis of CRCCs. Therefore, evaluation of the infiltration of PD-positive cells or Tregs in CRCC may be useful diagnostic tools for the selection of patients who could benefit from PD1- or Treg-based immunotherapy.     

Expression of DBC1 and Androgen Receptor Predict Poor Prognosis in Diffuse Large B Cell Lymphoma

BACKGROUND: Recently, deleted in breast cancer 1 (DBC1) has been suggested as a poor prognostic indicator of various human cancers and may possibly have a role as a coactivator of androgen receptor (AR). However, their roles in lymphoma are still unknown. MATERIALS AND METHODS: We investigated the effect of the expression of DBC1 and AR in diffuse large B cell lymphoma (DLBCL). Immunohistochemical expression of DBC1 and AR were evaluated in 101 DLBCL samples by tissue microarray. RESULTS: Positive expression of DBC1 and AR was seen in 73% and 70% of DLBCL, respectively. In total DLBCL patients, DBC1 and AR expression were significantly associated with high clinical stage, elevated serum lactate dehydrogenase levels, and high international prognostic index scores, and they predicted shorter overall survival (OS) and relapse-free survival (RFS) by univariate analysis. DBC1 expression was also an independent prognostic indicator by multivariate analysis (OS, P = .017; RFS, P = .004). Especially, both DBC1 and AR expression significantly correlated with shorter OS and RFS in non-germinal center B cell (non-GCB)-type DLBCL by univariate analysis. In multivariate analysis, DBC1 expression was an independent prognostic predictor for OS (P = .035) and AR expression significantly correlated with RFS (P = .005). CONCLUSION: We demonstrate that the expression of DBC1 and AR are significant prognostic indicators for DLBCL patients, especially for unfavorable non-GCB-type DLBCL.     

Rapid Genetic Analysis of Epithelial-Mesenchymal Signaling During Hair Regeneration

Hair follicle morphogenesis, a complex process requiring interaction between epithelia-derived keratinocytes and the underlying mesenchyme, is an attractive model system to study organ development and tissue-specific signaling. Although hair follicle development is genetically tractable, fast and reproducible analysis of factors essential for this process remains a challenge. Here we describe a procedure to generate targeted overexpression or shRNA-mediated knockdown of factors using lentivirus in a tissue-specific manner. Using a modified version of a hair regeneration model ^{5, 6, 11}, we can achieve robust gain- or loss-of-function analysis in primary mouse keratinocytes or dermal cells to facilitate study of epithelial-mesenchymal signaling pathways that lead to hair follicle morphogenesis. We describe how to isolate fresh primary mouse keratinocytes and dermal cells, which contain dermal papilla cells and their precursors, deliver lentivirus containing either shRNA or cDNA to one of the cell populations, and combine the cells to generate fully formed hair follicles on the backs of nude mice. This approach allows analysis of tissue-specific factors required to generate hair follicles within three weeks and provides a fast and convenient companion to existing genetic models.     

Discovery of potent inhibitors for interleukin-2-inducible T-cell kinase: structure-based virtual screening and molecular dynamics simulation approaches

In our study, a structure-based virtual screening study was conducted to identify potent ITK inhibitors, as ITK is considered to play an important role in the treatment of inflammatory diseases. We developed a structure-based pharmacophore model using the crystal structure (PDB ID: 3MJ2) of ITK complexed with BMS-50944. The most predictive model, SB-Hypo1, consisted of six features: three hydrogen-bond acceptors (HBA), one hydrogen-bond donor (HBD), one ring aromatic (RA), and one hydrophobic (HY). The statistical significance of SB-Hypo1 was validated using wide range of test set molecules and a decoy set. The resulting well-validated model could then be confidently used as a 3D query to screen for drug-like molecules in a database, in order to retrieve new chemical scaffolds that may be potent ITK inhibitors. The hits retrieved from this search were filtered based on the maximum fit value, drug-likeness, and ADMET properties, and the hits that were retained were used in a molecular docking study to find the binding mode and molecular interactions with crucial residues at the active site of the protein. These hits were then fed into a molecular dynamics simulation to study the flexibility of the activation loop of ITK upon ligand binding. This combination of methodologies is a valuable tool for identifying structurally diverse molecules with desired biological activities, and for designing new classes of selective ITK inhibitors.

Effect of heterologous xylose transporter expression in Candida tropicalis on xylitol production rate

Xylose utilization is inhibited by glucose uptake in xylose-assimilating yeasts, including Candida tropicalis, resulting in limitation of xylose uptake during the fermentation of glucose/xylose mixtures. In this study, a heterologous xylose transporter gene (At5g17010) from Arabidopsis thaliana was selected because of its high affinity for xylose and was codon-optimized for functional expression in C. tropicalis. The codon-optimized gene was placed under the control of the GAPDH promoter and was integrated into the genome of C. tropicalis strain LXU1 which is xyl2-disrupted and NXRG (codon-optimized Neurospora crassa xylose reductase) introduced. The xylose uptake rate was increased by 37–73 % in the transporter expression-enhanced strains depending on the glucose/xylose mixture ratio. The recombinant strain LXT2 in 500-mL flask culture using glucose/xylose mixtures showed a xylose uptake rate that was 29 % higher and a xylitol volumetric productivity (1.14 g/L/h) that was 25 % higher than the corresponding rates for control strain LXU1. Membrane protein extraction and Western blot analysis confirmed the successful heterologous expression and membrane localization of the xylose transporter in C. tropicalis.     

Structural and biochemical characterization of the broad substrate specificity of Bacteroides thetaiotaomicron commensal sialidase

Sialidases release the terminal sialic acid residue from a wide range of sialic acid-containing polysaccharides. Bacteroides thetaiotaomicron, a symbiotic commensal microbe, resides in and dominates the human intestinal tract. We characterized the recombinant sialidase from B. thetaiotaomicron (BTSA) and demonstrated that it has broad substrate specificity with a relative activity of 97, 100 and 64 for 2,3-, 2,6- and 2,8-linked sialic substrates, respectively. The hydrolysis activity of BTSA was inhibited by a transition state analogue, 2-deoxy-2,3-dehydro-N-acetyl neuraminic acid, by competitive inhibition with a K_i value of 35 μM. The structure of BSTA was determined at a resolution of 2.3 Å. This structure exhibited a unique carbohydrate-binding domain (CBM) at its N-terminus (a.a. 23–190) that is adjacent to the catalytic domain (a.a. 191–535). The catalytic domain has a conserved arginine triad with a wide-open entrance for the substrate that exposes the catalytic residue to the surface. Unlike other pathogenic sialidases, the polysaccharide-binding site in the CBM is near the active site and possibly holds and positions the polysaccharide substrate directly at the active site. The structural feature of a wide substrate-binding groove and closer proximity of the polysaccharide-binding site to the active site could be a unique signature of the commensal sialidase BTSA and provide a molecular basis for its pharmaceutical application.     

Si‐Encapsulating Hollow Carbon Electrodes via Electroless Etching for Lithium‐Ion Batteries

Remarkable improvements in the electrochemical performance of Si materials for Li‐ion batteries have been recently achieved, but the inherent volume change of Si still induces electrode expansion and external cell deformation. Here, the void structure in Si‐encapsulating hollow carbons is optimized in order to minimize the volume expansion of Si‐based anodes and improve electrochemical performance. When compared to chemical etching, the hollow structure is achieved via electroless etching is more advanced due to the improved electrical contact between carbon and Si. Despite the very thick electrodes (30 ～ 40 μm), this results in better cycle and rate performances including little capacity fading over 50 cycles and 1100 mA h g^?1 at 2C rate. Also, an in situ dilatometer technique is used to perform a comprehensive study of electrode thickness change, and Si‐encapsulating hollow carbon mitigates the volume change of electrodes by adoption of void space, resulting in a small volume increase of 18% after full lithiation corresponding with a reversible capacity of about 2000 mA h g^?1.     

Differential Immune Responses to Segniliparus rotundus and Segniliparus rugosus Infection and Analysis of Their Comparative Virulence Profiles

Two closely related bacterial species, Segniliparus rotundus and Segniliparus rugosus, have emerged as important human pathogens, but little is known about the immune responses they elicit or their comparative pathophysiologies. To determine the virulence and immune responses of the two species, we compared their abilities to grow in phagocytic and non-phagocytic cells. Both species maintained non-replicating states within A549 epithelial cells. S. rugosus persisted longer and multiplied more rapidly inside murine bone marrow-derived macrophages (BMDMs), induced more pro-inflammatory cytokines, and induced higher levels of macrophage necrosis. Activation of BMDMs by both species was mediated by toll-like receptor 2 (TLR2), followed by mitogen-activated protein kinases (MAPK) and nuclear factor κB (NF-κB) signaling pathways, indicating a critical role for TLR2 in Segniliparus-induced macrophage activation. S. rugosus triggered faster and stronger activation of MAPK signaling and IκB degradation, indicating that S. rugosus induces more pro-inflammatory cytokines than S. rotundus. Multifocal granulomatous inflammations in the liver and lung were observed in mice infected with S. rugosus, but S. rotundus was rapidly cleared from all organs tested within 15 days post-infection. Furthermore, S. rugosus induced faster infiltration of innate immune cells such as neutrophils and macrophages to the lung than S. rotundus. Our results suggest that S. rugosus is more virulent and induces a stronger immune response than S. rotundus.     

Use of Hangeul Twitter to Track and Predict Human Influenza Infection

Influenza epidemics arise through the accumulation of viral genetic changes. The emergence of new virus strains coincides with a higher level of influenza-like illness (ILI), which is seen as a peak of a normal season. Monitoring the spread of an epidemic influenza in populations is a difficult and important task. Twitter is a free social networking service whose messages can improve the accuracy of forecasting models by providing early warnings of influenza outbreaks. In this study, we have examined the use of information embedded in the Hangeul Twitter stream to detect rapidly evolving public awareness or concern with respect to influenza transmission and developed regression models that can track levels of actual disease activity and predict influenza epidemics in the real world. Our prediction model using a delay mode provides not only a real-time assessment of the current influenza epidemic activity but also a significant improvement in prediction performance at the initial phase of ILI peak when prediction is of most importance.     

Structure prediction of biological assemblies using GALAXY in CAPRI rounds 38-45

We participated in CARPI rounds 38-45 both as a server predictor and a human predictor. These CAPRI rounds provided excellent opportunities for testing prediction methods for three classes of protein interactions, that is, protein-protein, protein-peptide, and protein-oligosaccharide interactions. Both template-based methods (GalaxyTBM for monomer protein, GalaxyHomomer for homo-oligomer protein, GalaxyPepDock for protein-peptide complex) and ab initio docking methods (GalaxyTongDock and GalaxyPPDock for protein oligomer, GalaxyPepDock-ab-initio for protein-peptide complex, GalaxyDock2 and Galaxy7TM for protein-oligosaccharide complex) have been tested. Template-based methods depend heavily on the availability of proper templates and template-target similarity, and template-target difference is responsible for inaccuracy of template-based models. Inaccurate template-based models could be improved by our structure refinement and loop modeling methods based on physics-based energy optimization (GalaxyRefineComplex and GalaxyLoop) for several CAPRI targets. Current ab initio docking methods require accurate protein structures as input. Small conformational changes from input structure could be accounted for by our docking methods, producing one of the best models for several CAPRI targets. However, predicting large conformational changes involving protein backbone is still challenging, and full exploration of physics-based methods for such problems is still to come.